1. Fingerprinting the Datacenter Offense Mykell Miller, Gautam Bhawsar

2. Crisis Detection  Why don’t you detect unidentified crises?  How severe is each crisis?  May affect recovery method  May affect detection probability and method  Useful for operators to know  Fingerprints are averaged over epochs in the crisis  Everywhere else you use the median

3. Time to identification  What are you doing for 10 minutes?  Why have the time between epochs be 15 minutes?  Will shorter lead to more accurate or quicker identification?

4. Data Center  What is the configuration?  Fat tree, etc.  What kind of servers?  Type of servers affects type and frequency of crises  Using only Windows  Study cannot be applied to other OS

5. Data Set  Only 19 examples  8 types of crises had only 1 instance each  Training set of only 5 examples  No statistics on the user application being run  Don’t know if it’s representative